NCES Blog

Understanding the racial/ethnic equity of educational experiences is a vital objective. The National Assessment of Educational Progress (NAEP) High School Transcript Study (HSTS) collects and analyzes transcripts from a nationally representative sample of America’s public and private high school graduates, including information about the coursetaking of students by race/ethnicity.

In 2019, NCES collected and coded high school transcript data from graduates who participated in the grade 12 NAEP assessments. The participants included American Indian and Alaska Native (AI/AN) students as well as students from other racial/ethnic groups. The main HSTS 2019 results do not include AI/AN findings because the sample sizes for AI/AN students in earlier collection periods were too small to report NAEP performance linked to coursetaking measures. Therefore, this blog post serves to highlight available AI/AN data. Find more information about NAEP's race/ethnicity categories and trends.
 

About HSTS 2019

The 2019 collection is the eighth wave of the study, which was last conducted in 2009 and first conducted in 1987. Data from 1990, 2000, 2009, and 2019—representing approximately decade-long spans—are discussed here. Data from HSTS cover prepandemic school years.
 

How many credits did AI/AN graduates earn?

For all racial/ethnic groups, the average number of Carnegie credits AI/AN graduates earned in 2019 was higher than in 2009 and earlier decades (figure 1). AI/AN graduates earned 27.4 credits on average in 2019, an increase from 23.0 credits in 1990. However, AI/AN graduates earned fewer overall credits in 2019 than did Asian/Pacific Islander, Black, and White graduates, a pattern consistent with prior decades.

Figure 1. Average total Carnegie credits earned by high school graduates, by student race/ethnicity: Selected years, 1990 through 2019 

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* Significantly different (p < .05) from American Indian/Alaska Native group in the given year.                                                              
+ Significantly different (p < .05) from 2019 within racial/ethnic group.                                                   
NOTE: Race categories exclude Hispanic origin. Black includes African American, Hispanic includes Latino, and Pacific Islander includes Native Hawaiian.                                                               
SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) High School Transcript Study, various years, 1990 to 2019.

In 2019, the smaller number of total credits earned by AI/AN graduates—compared with graduates in other racial/ethnic groups—was driven by the smaller number of academic credits earned. On average, AI/AN graduates earned about 1 to 3 academic credits less (19.3 credits) than graduates in other racial/ethnic groups (e.g., 22.2 for Asian/Pacific Islander graduates and 20.6 for Hispanic graduates) (figure 2). In contrast, AI/AN graduates earned more or a similar number of credits in career and technical education (CTE) (3.6 credits) and other courses (4.5 credits) compared with graduates in other racial/ethnic groups.

Figure 2. Average Carnegie credits earned by high school graduates in academic, career and technical education (CTE), and other courses, by student race/ethnicity: 2019

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* Significantly different (p < .05) from American Indian/Alaska Native group.                                                                            
NOTE: Race categories exclude Hispanic origin. Black includes African American, Hispanic includes Latino, and Pacific Islander includes Native Hawaiian.                                                                                                                                                            
SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) High School Transcript Study, 2019.            

What was the grade point average (GPA) of AI/AN graduates?

As with credits earned, GPA has been generally trending upward since 1990. AI/AN graduates had an average GPA of 2.54 in 1990 and an average GPA of 3.02 in 2019 (figure 3). Unlike with credits earned, however, the average GPA for AI/AN graduates was between the GPA of graduates in other racial/ethnic groups in 2019: it was lower than the GPAs for Asian/Pacific Islander and White graduates and higher than the GPAs for Black and Hispanic graduates.

Figure 3. Average overall grade point average (GPA) earned by high school graduates, by student race/ethnicity: Selected years, 1990 through 2019

[click to enlarge image]

* Significantly different (p < .05) from American Indian/Alaska Native group in the given year.                                            
+ Significantly different (p < .05) from 2019 within racial/ethnic group.                                                                                       
NOTE: Race categories exclude Hispanic origin. Black includes African American, Hispanic includes Latino, and Pacific Islander includes Native Hawaiian.                                                                                                                                                            
SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) High School Transcript Study, various years, 1990 to 2019.

What curriculum level did AI/AN graduates reach?

HSTS uses curriculum levels to measure the rigor of high school graduates’ coursework as a potential indicator of college preparedness. There are three curriculum levels: standard, midlevel, and rigorous. Students who did not meet the requirements for a standard curriculum are considered to have a “below standard” curriculum.

Reflecting the smaller numbers of academic credits earned by AI/AN graduates, as described above, a lower percentage of AI/AN graduates reached the rigorous level (the highest level): only 5 percent of AI/AN graduates had completed a rigorous curriculum in 2019, compared with 10 percent of Hispanic, 13 percent of White, and 28 percent of Asian/Pacific Islander graduates (table 1). Similarly, a lower percentage of AI/AN graduates completed a midlevel curriculum than did White, Black, or Hispanic graduates. At the standard and below-standard levels, therefore, AI/AN graduates were overrepresented relative to most other groups.

Table 1. Percentage distribution of high school graduates across earned curriculum levels, by student race/ethnicity: 2019

* Significantly different (p < .05) from American Indian/Alaska Native group.
NOTE: Details may not sum to total due to rounding. A graduate who achieves the standard curriculum earned at least four Carnegie credits of English and three Carnegie credits each of social studies, mathematics, and science. A graduate who achieves a midlevel curriculum earned at least four Carnegie credits in English, three Carnegie credits in mathematics (including credits in algebra and geometry), three Carnegie credits in science (including credits in two among the subjects of biology, chemistry, and physics), three Carnegie credits in social studies, and one Carnegie credit in world languages. A graduate who achieves a rigorous curriculum earned at least four Carnegie credits in English, four Carnegie credits in mathematics (including credits in precalculus or calculus), three Carnegie credits in science (including credits in all three subjects of biology, chemistry, and physics), three Carnegie credits in social studies, and three Carnegie credits in world languages. Graduates with curriculum that do not meet the requirements for the standard level are considered as “Below standard.” Race categories exclude Hispanic origin. Black includes African American, Hispanic includes Latino, and Pacific Islander includes Native Hawaiian.
SOURCE: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics, National Assessment of Educational Progress (NAEP) High School Transcript Study, 2019.

Explore the HSTS 2019 website to learn more about the study, including how courses are classified, grade point average is calculated, and race/ethnicity categories have changed over time. Be sure to follow NCES on X, Facebook, LinkedIn, and YouTube and subscribe to the NCES News Flash to stay informed about future HSTS data and resources.

By Ben Dalton, RTI International, and Robert Perkins, Westat

NCES is committed to providing reliable and up-to-date national-level estimates of bullying. As such, a new set of web tables focusing on bullying victimization at school was just released.  

These tables use data from the School Crime Supplement to the National Crime Victimization Survey, which collects data on bullying by asking a nationally representative sample of students ages 12–18 who were enrolled in grades 6–12 in public and private schools if they had been bullied at school. This blog post highlights data from these newly released web tables.

Some 19 percent of students reported being bullied during the 2021–22 school year. More specifically, bullying was reported by 17 percent of males and 22 percent of females and by 26 percent of middle school students and 16 percent of high school students. Moreover, among students who reported being bullied, 14 percent of males and 28 percent of females reported being bullied online or by text.

Students were also asked about the recurrence and perpetrators of bullying and about the effects bullying has on them. During the 2021–22 school year, 12 percent of students reported that they were bullied repeatedly or expected the bullying to be repeated and that the bullying was perpetrated by someone who was physically or socially more powerful than them and who was not a sibling or dating partner. When these students were asked about the effects this bullying had on them,

• 38 percent reported negative feelings about themselves;
• 27 percent reported negative effects on their schoolwork;
• 24 percent reported negative effects on their relationships with family and friends; and
• 19 percent reported negative effects on their physical health.

Explore the web tables for more data on how bullying victimization varies by student characteristics (e.g., sex, race/ethnicity, grade, household income) and school characteristics (e.g., region, locale, enrollment size, poverty level) and how rates of bullying victimization vary by crime-related variables such as the presence of gangs, guns, drugs, alcohol, and hate-related graffiti at school; selected school security measures; student criminal victimization; personal fear of attack or harm; avoidance behaviors; fighting; and the carrying of weapons.

Find additional information on this topic in the Condition of Education indicator Bullying at School and Electronic Bullying. Plus, explore more School Crime and Safety data and browse the Report on Indicators of School Crime and Safety: 2022.

Recently, the Office of the Chief Statistician, within the Office of Management and Budget (OMB), released an initial set of recommended revisions for OMB’s Statistical Policy Directive No. 15 (SPD 15), which provides the statistical standards for collecting and reporting race and ethnicity data across federal agencies. The revisions were proposed by an Interagency Technical Working Group.

This is the next step in a process that began last summer with a simple goal: to ensure that the standards better reflect the diversity of the American people. The initial proposals—developed by federal government staff representing more than 20 agencies—include the following:

• collecting race and ethnicity together with a single question
• adding a response category for Middle Eastern and North African that is separate and distinct from the “White” category
• updating SPD 15’s terminology, definitions, and question wording

These recommendations are preliminary—not final—and they do not represent the positions of OMB or the agencies participating in the Working Group.

The Working Group is committed to a full, transparent revision process and remains on track to reach the goal of completing these important revisions by the summer of 2024.

The Working Group Wants to Hear Directly From the American People

The public’s participation in this process will play a critical role in helping the Working Group improve the way federal agencies safely and accurately collect and use information on the race and ethnicity of our diverse population.

Interested stakeholders can read the full Federal Register Notice and provide comments, participate in one of the Working Group’s bi-monthly virtual listening sessions or upcoming virtual town halls, and schedule a listening session.

Be sure to follow NCES on Twitter, Facebook, LinkedIn, and YouTube and subscribe to the NCES News Flash to receive notifications about the revision process and opportunities to engage with the Working Group.

The Integrated Postsecondary Education Data System (IPEDS) is a comprehensive federal data source that collects information on key features of higher education in the United States, including characteristics of postsecondary institutions, college student enrollment and academic outcomes, and institutions’ employees and finances, among other topics.

The National Center for Education Statistics (NCES) has created a new resource page, Student Cohorts and Subgroups in IPEDS, that provides data reporters and users an overview of how IPEDS collects information related to postsecondary students and staff. This blog post highlights key takeaways from the resource page.

IPEDS survey components collect counts of key student and staff subgroups of interest to the higher education community.

Data users—including researchers, policy analysts, and prospective college students—may be interested in particular demographic groups within U.S. higher education. IPEDS captures data on a range of student and staff subgroups, including race/ethnicity, gender, age categories, Federal Pell Grant recipient status, transfer-in status, and part-time enrollment status.

The Outcome Measures (OM) survey component stands out as an example of how IPEDS collects student subgroups that are of interest to the higher education community. Within this survey component, all entering degree/certificate-seeking undergraduates are divided into one of eight subgroups by entering status (i.e., first-time or non-first-time), attendance status (i.e., full-time or part-time), and Pell Grant recipient status.

Although IPEDS is not a student-level data system, many of its survey components collect counts of students and staff by subgroup.

Many IPEDS survey components—such as Admissions, Fall Enrollment, and Human Resources—collect data as counts of individuals (i.e., students or staff) by subgroup (e.g., race/ethnicity, gender) (exhibit 1). Other IPEDS survey components—such as Graduation Rates, Graduation Rates 200%, and Outcome Measures—also include selected student subgroups but monitor cohorts of entering degree/certificate-seeking students over time to document their long-term completion and enrollment outcomes. A cohort is a specific group of students established for tracking purposes. The cohort year is based on the year that a cohort of students begins attending college.

Exhibit 1. IPEDS survey components that collect counts of individuals by subgroup

IPEDS collects student and staff counts by combinations of interacting subgroups.

For survey components that collect student or staff counts, individuals are often reported in disaggregated demographic groups, which allows for more detailed understanding of specific subpopulations. For example, the Fall Enrollment (EF) and 12-month Enrollment (E12) survey components collect total undergraduate enrollment counts disaggregated by all possible combinations of students’ full- or part-time status, gender, degree/certificate-seeking status, and race/ethnicity. Exhibit 2 provides an excerpt of the EF survey component’s primary data collection screen (Part A), in which data reporters provide counts of students who fall within each demographic group indicated by the blank cells.

Exhibit 2. Excerpt of IPEDS Fall Enrollment (EF) survey component data collection screen for full-time undergraduate men: 2022­–23

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NOTE: This exhibit reflects the primary data collection screen (Part A) for the 2022–23 Fall Enrollment (EF) survey component for full-time undergraduate men. This screen is duplicated three more times for undergraduate students, once each for part-time men, full-time women, and part-time women. For survey materials for all 12 IPEDS survey components, including complete data collection forms and detailed reporting instructions, visit the IPEDS Survey Materials website.

As IPEDS does not collect data at the individual student level, these combinations of interacting subgroups are the smallest unit of information available in IPEDS. However, data users may wish to aggregate these smaller subgroups to arrive at larger groups that reflect broader populations of interest.

For example, using the information presented in exhibit 2, a data user could sum all the values highlighted in the green column to arrive at the total enrollment count of full-time, first-time men. As another example, a data user could sum all the values highlighted in the blue row to determine the total enrollment count of full-time Hispanic/Latino men. Note, however, that many IPEDS data products provide precalculated aggregated values (e.g., total undergraduate enrollment), but data are collected at these smaller units of information (i.e., disaggregated subgroup categories).

Student enrollment counts and cohorts align across IPEDS survey components.

There are several instances when student enrollment or cohort counts reported in one survey component should match or very closely mirror those same counts reported in another survey component. For example, the number of first-time degree/certificate-seeking undergraduate students in a particular fall term should be consistently reported in the Admissions (ADM) and Fall Enrollment (EF) survey components within the same data collection year (see letter A in exhibit 3).

Exhibit 3. Alignment of enrollment counts and cohorts across IPEDS survey components

For a full explanation of the alignment of student counts and cohorts across IPEDS survey components (letters A to H in exhibit 3), visit the Student Cohorts and Subgroups in IPEDS resource page.

Be sure to follow NCES on Twitter, Facebook, LinkedIn, and YouTube, follow IPEDS on Twitter, and subscribe to the NCES News Flash to stay up-to-date on IPEDS data releases and resources.

By Katie Hyland and Roman Ruiz, AIR

As the school year comes to a close, many families are considering opportunities to continue learning over the summer months. Summer learning has often been seen as a way to supplement instruction during the regular school year. The U.S. Department of Education’s “COVID-19 Handbook” notes that summer learning “can offer another opportunity to accelerate learning, especially for those students most impacted by disruptions to learning during the school year.” Data from the Household Pulse Survey (HPS), which NCES developed in partnership with the U.S. Census Bureau and other federal statistical agencies, explores access to summer learning opportunities by school type, racial/ethnic group, household educational attainment level, and income level.

The HPS¹ provides data on how people’s lives have been impacted by the coronavirus (COVID-19) pandemic. Phase 3.2 of the HPS introduced questions on the summer education activities of children enrolled in public or private school or homeschooled, following the end of the normal school year in spring 2021. Adults 18 years old and over who had children under 18 in the home enrolled in school were asked if any of the children had attended a traditional summer school program because of poor grades; attended a summer school program to help catch up with lost learning time during the pandemic; attended school-led summer camps for subjects like math, science, or reading; and/or worked with private tutors to help catch up with lost learning time during the pandemic. Adults were allowed to select all categories that applied. Data from Phase 3.2 of the HPS, covering September 15 to 27, 2021, are discussed in this blog post.

Among adults with children enrolled in public or private school or homeschooled, 26 percent reported children were enrolled in any summer education activities after the end of the normal school year in spring of 2021 (figure 1). The most reported summer education activity was attending a summer school program to catch up on lost learning time during the pandemic (10 percent). Eight percent reported children attended school-led summer camps for subjects like math, science, or reading and 7 percent each reported children attended a traditional summer school program because of poor grades or worked with private tutors to catch up with lost learning time during the pandemic.

Figure 1. Among adults 18 years old and over who had children under age 18 in the home enrolled in school, percentage reporting participation in summer education activities after the end of the normal school year in spring of 2021, by type of summer activity: September 15 to 27, 2021